微结构模芯的精密磨削及其在微注塑成形中应用

针对微结构聚合物元器件的批量化生产与制造效率低等问题，采用精密修整成V形尖端的金刚石砂轮，在自润滑性和脱模性良好的钛硅碳陶瓷模芯表面加工制造出形状精度可控的V沟槽阵列结构，然后利用微注塑成形工艺将模芯表面的V沟槽阵列结构一次成形复制到聚合物表面，高效注塑成形制造出倒V形阵列结构的聚合物工件。分析了微模芯的表面加工质量与形状精度，研究了熔体温度、注射速度、保压压力、保压时间等微注塑成形工艺参数对微结构聚合物注塑成形角度偏差和填充率的影响。实验结果表明：通过微细磨削加工技术和微注塑成形工艺可以高效率、高精度地制造出规则整齐的微结构注塑工件，注射速度对微成形角度偏差的影响最大，保压压力对微成形填充率的影响最大，微结构模芯的微细磨削形状精度值为4.05 μm，微成形的最小角度偏差和最大填充率分别为1.47°和99.30%。     

松河井田多煤层资源开发条件及合采储层伤害特征

为了降低煤层气井排采过程中的储层伤害,通过分析松河井田的资源开发条件及煤层气井排采数据,总结各排采阶段不合理排采控制引起的储层伤害特征,提出不同排采阶段合理的排采工艺对策。分析结果表明:松河井田煤层气资源丰度达到2.09×10^8m^3/km^2,煤层气资源开发条件较好;松河井田多煤层合层排采过程中,不合理排采控制工艺对煤层气井的产气量影响较大;排采初期以速敏伤害为主,排采中期以气锁和应力闭合伤害为主;修井作业及停抽期间,气锁效应及应力闭合对煤层造成伤害的可能性增大。合理的排采控制能够有效降低煤层气井的储层伤害,提高煤层气井产气量。     

旋转式采煤工艺在煤矿生产中的应用

采煤工艺作为煤矿正常生产的核心,直接关系到综采作业的效率、煤炭回采率和综采作业的安全性,随着对综采作业要求的不断提高,旋转式采煤工艺在煤矿井下的应用范围也不断扩大。以黄家沟煤业1205综采作业面为分析对象,对旋转式采煤工艺在井下的应用情况进行了研究,为优化综采方法、提升综采作业效率和煤炭回采率奠定基础。     

The control of paracetamol particle size and surface morphology through crystallisation in a spray dryer

The parameters governing the crystallisation of paracetamol using various conventional techniques has been extensively studied, however the factors influencing the drug crystallisation using spray drying is not as well understood. The aim of this work was to investigate the crystallisation of an active pharmaceutical ingredient through evaporative crystallisation using a spray dryer to study the physicochemical properties of the drug and to use semi-empirical equations to gain insight into the morphology and particle size of the dried powder. Paracetamol solutions were spray dried at various inlet temperatures ranging from 60 °C to 120 °C and also from a series of inlet feed solvent compositions ranging from 50/50% v/v ethanol/water to 100% ethanol and solid-state characterisation was done. The size and morphology of the dried materials were altered with a change in spray drying parameters, with an increase in inlet temperature leading to an increase in particle Sauter mean diameter (from 3.0 to 4.4 µm) and a decrease in the particle size with an increase in ethanol concentration in the feed (from 4.6 to 4.4 µm) as a result of changes in particle density and atomised droplet size. The morphology of the dried particles consisted of agglomerates of individual crystallites bound together into larger semi-spherical agglomerates with a higher tendency for particles having crystalline ridges to form at higher ethanol concentrations of the feed.     

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (Q_L) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.     

福建某低品位金矿新型浸金剂浸金试验

福建某斑岩型金矿品位低、规模大,金主要以自然金形式存在,可见金的粒度较粗,为高效利用该低品位金矿,开展新型浸金剂金蝉全泥浸出试验和柱浸试验,结果表明：全泥浸出在磨矿细度为-0.074 mm占80%、矿浆浓度25%、加石灰调pH 值11.0左右、初始金蝉浓度为500 mg/L和过程中控制金蝉浓度不小于300 mg/L条件下浸出20 h,金的浸出率为93.43%,金蝉耗量为1.02 kg/t；柱浸在矿石粒度为-30 mm条件下喷淋浸出23天,金累计浸出率和金蝉累计耗量分别为86.54%和1.22 kg/t。     

Effect of different fibres on texture,rheological and sensory properties of acid casein processed cheese sauces

The objective of this study was the evaluation of different fibres (bamboo, acacia, potato or citrus) addition on texture, rheological and sensory properties of acid casein processed cheese sauces. Fibres used in production of sauces had an impact on the texture, viscosity, viscoelastic and sensory properties. The largest increase in viscosity was observed in products with addition of potato fibre, which have good water holding and adsorption capacity. Processed cheese sauce with the addition of citrus fibre was characterised by the highest values in general, and the increase of this feature in the tested samples was regular. Adhesiveness was the highest in products with 1% addition of every fibre. The lowest values of viscosity single shear, G′ and G″ moduli, among all tested, had sauces with acacia fibre. Moreover, they had the most thin liquid consistency, which was different from preferred one.     

Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

机载通信电台通电老炼检测系统设计与实现

为保证航材备件的完好率，解决仓储机载通信电台长期不通电导致的装备性能下降甚至出现故障的问题，综合运用自动测试、虚拟仪器、面向信号设计等技术，以计算机为核心，以PXI仪器、GPIB仪器为依托，以多种总线接口为纽带，构建了一种可靠性高、通用性好、操作简便、可扩展性强的自动化通电老炼平台。通过在航材仓库中使用，证明该电台老炼检测系统降低了仓储通信电台的失效率，提高了仓储电台的完好率。     

基于梯度分布调节策略的Xgboost算法优化

为了解决集成学习模型Xgboost在二分类问题中少数类检出率低的问题，提出了基于梯度分布调节策略的改进的Xgboost算法——LCGHA-Xgboost。首先，通过定义损失贡献（LC）来模拟Xgboost算法中样本个体的损失量；而后，通过定义损失贡献密度（LCD）来衡量Xgboost算法中样本被正确分类的难易程度；最后，提出了梯度分布调节算法LCGHA，依据LCD动态调整样本个体的一阶梯度分布，间接地增大难分样本（主要存在于少数类中）的损失量，减小易分样本（主要存在于多数类中）的损失量，使Xgboost算法偏向对难分样本的学习。实验结果表明,与Xgboost、GBDT、随机森林（Random_Forest）这三大集成学习算法相比，LCGHA-Xgboost算法在多个UCI数据集上的召回率（Recall）值有5.4%~16.7%的提高，AUC值有0.94%~7.41%的提高；在垃圾网页数据集WebSpam-UK2007和DC2010数据集上所提算法的Recall值更是有44.4%~383.3%的提高，AUC值有5.8%~35.6%的提高。LCGHA-Xgboost算法可以有效提高对少数类的分类检出能力，减小少数类的分类错误率。